Filed by Urgent.ly Inc.
Pursuant to Rule 425 under the Securities Act of 1933
and deemed filed pursuant to 14a-12
under the Securities Exchange Act of 1934
Subject Company: Otonomo Technologies Ltd.
Commission File No.: 001-40744
Date: August 10, 2023
Otonomo / Urgent.ly
Presentation delivered at the J.P. Morgan 2023 Auto Conference on Wednesday, August 09, 2023 at 4:35 PM
If you want to take your seats, we can get going with the next presentation. Once again, I’m Ryan Brinkman, US Autos Analyst at J.P. Morgan. We’re excited to get going with Otonomo and Urgently, which are in the process of merging together.
Here we have Matt Booth, CEO of Urgently, and Ben Volkow, CEO and co-founder of Otonomo. I’m going to turn it over to them. They’re going to walk us through a presentation, and then we’ll sit down for some chat.
Hi, everyone. Thank you for the time today. Ryan, thank you for having us here. Before we start, I read a quick, safe harbor statement I was requested to read.
Today’s discussion will include forward-looking statements related to Otonomo and Urgently’s current plans and expectations, which are subject to certain risks and uncertainties. Actual results may differ materially due to various important factors, including those described on slide two through four of our presentation and in the risk factor section of our most recent form S4 and form S1, and other SEC filings. Those forward-looking statements represent our views as of this meeting and should not be relied upon as representing our views as of any subsequent date. We undertake no obligation to publicly update this statement. Thank you for your patience.
I will talk a bit about Otonomo, and really why Otonomo and Urgently are merging, and then Matt will present Urgently in more detail, a very, very interesting company, and we’ll leave time for Q&A.
Otonomo went public two years ago. We really built the biggest or the first and biggest mobility platform out there. What does mobility platform mean? It means that we are connecting to OEMs, to the car manufacturers’ databases, and getting all the connected cars’ data. Of course, based on privacy and consent, we use it in order to deliver value to the drivers.
Sharing this data with smart cities, or insurance companies, or dealerships, or fleet managers to create additional value. Cars are like a phone today. They come out of the dealership with a small modem and a tiny sim, and they all the time send a lot of data.
All this data could be used really to create new use cases, to offer value for drivers, to improve the environment, to drive safety. Things like usage-based insurance where you pay based on the actual miles you drove or your driving style based on the data from the vehicle, or predictive maintenance for fleets, so you can understand and find out problems before they happen and handle them. Or for rental companies, nobody wants to take a car, find out there’s a problem, do a U-turn, and drive another 60 miles to bring it back to the office.
Otonomo understood that we need to grow faster. Part of it is really the reason that we are merging with the Urgently. We saw a lot of synergy with our technology and connected car data and expertise, and really the roadside business that Urgently have built. I’ll keep it short and sweet, and I’ll let Matt take the stage and present Urgently in more detail.
Thanks, Ben. As Ben said, we’re going to go through a quick presentation about Urgently and then some things about Otonomo. We’re going to hold questions in the end, but if anyone has any questions as we go through it, feel free to jump in.
Urgently, its job is based on saving stranded drivers. If you’re familiar with the roadside assistance space where you’ve driven a car and it’s broken down and someone’s coming out and gotten you. AAA is the largest subscription business in the US with 61 million customers, and then there’s a handful of other legacy customers that do this on a B2B basis.
We’re primarily focused on the B2B side of the business. The company was founded about 10 years ago. Typical story, a bunch of people in a coffee shop. They were looking at companies like Uber and said, “Hey, all these companies are revolutionizing the customer experience around these digital apps. Let’s build a digital app and let’s do what Uber did for roadside assistance.”
That turned into a pilot with a major OEM and that, of course like all good entrepreneurs at the time, they pivoted the business, eventually won 100 percent of that OEM business. Along the way, it started to build a pretty impressive portfolio of other customer wins.
On the cap table and in customers, Porsche is an investor, BMW is an investor, Jaguar Land Rover is an investor. One of the world’s largest rental car companies is an investor and a customer. Then, of course, American Tire Distributors and a handful of other smaller PE companies.
It’s a strange business. As we look at the economy and there’s talk about a recession, this business is somewhat anti-cyclical. The more that the economy starts to turn down, the more people put off repairs in their car. That means the more they’re going to break down. Again, when you buy a new car from, say, BMW or something like that, they all come with warranty.
When you break down in a car like that and you hit the button or you call their call center, many of those calls come to us and we run the service fleet to go out and do the repairs on the side of the road or do the towing. We don’t own those vehicles. We have a partnership group of about 80,000 drivers that covers all of North America, so we can recover any vehicle 24, 7, 365.
It’s really the OEMs that gave us the scale on this business. Had tremendous growth along the way. Last year, we did about $188 million. We’re super focused on how do we drive the customer experience and make it exceptional. We obsess on that a lot to make sure that we’re doing a great job because it’s a small business. There is probably 50 key customers that really matter and it’s really a small world where if we do a good job, we get another customer. It’s a really big pipeline. We’ll go through a little bit of that in a little while.
In terms of customer service and how we measure it, we run either NPS or we run CSAT. Customer service scores on every single job. We get a really good response rate. Average is about 4.5 out of 4.6 average customer rating, which if you think about it, you’re breaking down, you’re having a bad day. The fact that we can get someone to a place and they’re actually moderately happy is a big win.
Now, one of the reasons that we started this business is because we believed that this business is primarily run by legacy customers that started decades and decades ago. All of us come from the software world. We believe that with a data set that’s proprietary, we could put machine learning and data analytics on top of it and drive real value.
We’ve seen that in our margin expansion that I’ll go through in a minute. We’ve seen that in our improved customer service scores, and I’ll go through that in a minute too.
It’s really this adding technology to what we’re thinking about is a global services and support business, along with what Ben has already built with Otonomo and the Floow, is really synergistic and allows us to cross-sell across some different companies.
What you’re looking at here is, this is a snapshot of a typical morning at Urgently. Every single one of those blue dots represents a live job that’s in flight. All of our partners have a version of this. If you go to someone like BMW, as an example, they have a version of this in their office where they can go and they can click on any job for their customer. They can see in real-time what’s happening to the customer, what the reason for the disablement is. If you drill into it, you can see superimposed in LA, Atlanta, and New York. You get down into a small geographic radius, you can actually see the truck moving to come out to service the customer. And really, the business is founded on this idea of radical transparency, which is we’ll show everything.
This is a hard business. Not every job goes perfect every single time. Because it’s all based on really sophisticated data analytics and machine learning, it allows us to pay attention to the small amount of jobs that are not going well. We can redirect the customer service team to say, “Hey, Ben has a problem. Their repair vehicle is caught in traffic,” or, “Tim, his fleet vehicle is down and needs to get back up and we need to help Amazon get the packages back up.” It really allows us to manage the pieces of the business that are really pretty critical.
We believe, and we have shown in our margin improvement, this data asset that we have underneath it is actually pretty important for driving really substantially high customer service scores and improving the overall economics of the business.
Now, we’ve had a tremendous growth. We’ve done about 4.5 million jobs since the inception. We did almost 1.3 million last year. In a strange way, this business has never had a problem with growth. We’ve always had so many customers coming in that we’ve had to back off as we’ve gone through different fund raises. Now that we’re going to close this, we can start to put the gas back on the growth again.
In terms of our position in the market, we believe that we can manage and deliver real-world services that include the connected aspects of the vehicle. Ben talked about how signals are coming off the vehicle. If you go back and you look at Ben’s business from some years ago, one of the things that they originally believed is that out in the future, ‘25, ‘26, ‘27, there would be a decent preponderance of jobs that came from the services aspect of it. It’s this joining of data coming off the vehicle and then there’s matching of the service network to it, so we can algorithmically pinpoint problems with the cars before there are actually problems.
As an example, a lot of these cars will detect if you hit a pothole. We know the car is going to have a flat tire in 60 miles. We can actually send a service vehicle out to meet you at your work or your job or wherever you’re going, so you’re not inconvenienced.
Ultimately, that’s the goal of the business is to completely reduce, if not eliminate, any of these reactive roadside pieces and really move into a software business where we’re predicting what’s going to go, where it’s going to move, and how it’s going to change.
In terms of the vision, and the reason that we like this combination so much is, if you think about Urgently and where we sit, we sit at the end, on the reactive piece, which is your car is already broken down, you need help. The reason we like what Otonomo has is because it comes before the breakdown.
Before the car breaks down, there’s a signal that comes off and says, “Hey, fleet manager. There’s a problem with the vehicle. We need to get a service company out.” Before that, Ben was very prescient, and he bought a company called the Floow in Sheffield. Sheffield has a lot of data analytics around Europe that will start to expand in other places. They measure every single road in Europe down to three-meter segments, and they measure driving behavior and driver scoring, so you can imagine a fleet use case. Hey, you’re driving on roads that are not safe. You’re cornering too much. The vehicle sending signals that you’re going to have a breakdown so we can start to eliminate and process with software all these breakdowns that are starting to transpire and start to group these together in something that’s really a pretty good competitive moat that no one else we believe has.
Ben mentioned this previously. The cars today, they’re basically a mobile phone. They are sensors on wheels. All kinds of data come off. The weather comes off, the status of the vehicle, if there’s a collision, what’s wrong with it, the geo position.
Because a lot of our partners are investors, we’ll be able to build new use cases that we believe will enable the subscription market to accelerate our growth. You’re probably all familiar with Stellantis, GM, Ford. Depending on the company you’re talking about, they all have subscription targets for 2030, anywhere from a billion dollars in subscription revenue to $20 billion. There’s a piece that we hope to play in this as we start to open up the software and the model to some of these automakers and some of our partners.
In terms of the Floow that I mentioned, I already work with a lot of big insurance companies in the UK and also in the US. They already do driver scoring for fleets, so they can tell you your fleet driver is driving too fast. They can tell you that if you start to slow down and drive better, your insurance rates will drop so they do a lot of usage-based insurance. Then crash detection, which a lot of people do, we’re starting to meld these things together.
Again, a lot of people talk about this concept of AI and machine learning. I’ll just be upfront. I’m not a big believer in scraping the Web to do machine learning and artificial intelligence. It doesn’t really do a lot. In these very specific use cases where companies have proprietary data sets, where you can apply very specific knowledge to improve the experience, they’ll become very valuable. Over time, we’ll start to exploit more and more and more of the specificity around algorithms and how we produce and create leverage in the business.
Now, in terms of the market, really big pipeline in the US. It’s a really big market here. It’s over $2 billion in B2B business. The global market opportunity is over $100 billion.
Then, on the piece that I mentioned before, this subscription business, and I spent some time at Interactive Corp a long, long time ago where we bought Match.com and a handful of other businesses. We love this idea of enabling partners and helping them build subscription businesses, great businesses, reoccurring revenue, great for valuations, all those kind of things.
We’re going to start to explore more and more with this. It’s one of those things where we start with partners in the typical roadside and then we move into other adjacent opportunities with them, some of which are subscription and others. Pretty big, robust pipeline to both expand the business and then expand the margin.
In terms of the company, we have focused a lot since last year, mid-July, on getting the business to what we’ll call operational excellence and move it to profitability. Probably not a surprise to many people in this room. 15 years of zero interest rates means it’s pretty easy to go raise money. Those days are now gone.
This reminds me of a lot of back in 2000 when I was at City Search and Interactive Corp. Everyone’s super happy one day. The stock’s really high. The next day, you come in and mascara is running down people’s faces and the market’s imploded and all these companies are starting to have problems. Those days are coming back again.
Meaning that there is going to be a focus again on profitability and making sure that there’s cash flow being produced in businesses. Now, that’s great, because, with us, we’re on a trajectory to get there pretty soon. There’s going to be some pretty spectacular companies that are out there that, through no fault of their own, they raised money at pretty high valuations. They’re not going to be able to get a series B or a series C. We’ll have the right capital structure where we can go out and say, “Hey, are these bolt-on acquisitions? Do we want to acquire them? Do we want to move into more global markets?” We’re pretty bullish on that.
In terms of the performance of the business, improved 23 percent quarter over quarter, which was great. The real story is, I mentioned, machine learning. We spent a lot of time on data and data analytics. While revenue was up $10 million, we saw a 279 percent improvement in gross profits.
We’re super focused on now that we’ve achieved scale in North America, how do we become more efficient, and how do we drive more profit to the business?
Gross margin went from 6% to 19% quarter over quarter, and operating loss went from $16 million to $10 million. Now, on the $10 million, if you pull our filings apart, what you’ll see is roughly half of the $10 million is in transaction costs so it’s actually better than what it looks like in terms of what’s on this slide. Then the real story is cash burn. We’ve reduced cash burn pretty substantially. Cash used in operating activities for quarter ending March 31, 2022 was $15 million, and Q1 2023 was $1 million. We’re really starting to see now that we’ve done 3.5 million jobs, we did 1.3 million last year, we’re really starting to see the profitability catch up. We started to see the investment that we put into product and tech, start to pay off. We’re pretty bullish on and excited about where we’re going. With that, I’ll take any questions. Happy to answer anything.
Are your customers the people who are stranded on the side of the road, or is it the automakers that are looking to have? How is it brand—as Urgently or as like Porsche Roadside Service?
Yes, so Porsche is an investor. They’re not a customer yet, just to be clear. Coming soon, we hope. Since we run a B2B business, we view — I’ll use BMW as an example — as an extension of their brand, and we take it very seriously. It’s branded. It depends on the partner. Sometimes it’s co-branded with Urgently. The customer in terms of who pays us, BMW pays us for the service, but they will pay us for the service because we do a great job servicing their customers. If you go talk to our customers, that’s what they’ll say. They say that we do a fantastic job at that. We ask the end customer who had the disablement, “What did you think?” We report that up to our partners and we take that pretty seriously. Again, a lot of companies talk about customer service, but we live and die by how well we do on that because we know that they’ll refer other people to us.
How do you get those really independent contractors and tow truck drivers? How do you ensure that they do a good job?
It’s a good question. We work with about 12,000, 13,000 companies or so. Multiple people drive the vehicle, so there’s not one driver per vehicle. It rounds up to about 80,000 drivers across North America.
When we got our first OEM partner, we called him up and said, “Hey, we are selling such OEM partner. We’re going to give you jobs in New York and we’re going to pay you $100 a job.” They go, “No, you’re going to pay us $300 a job.” We’re like, “We’re going to pay you $300 a job.”
Then as we achieve scale, we started to rationalize the economics of the business. We run everyone through a set of qualifications. They have to come through minimum insurance, the background check, and a whole bunch of other things that they have to do, and years of operating history in order to get in the platform.
It’s a strange kind of business, where now that we have the demand, the supply comes along naturally with it. As an example, with the partners that we had, if we were to launch in, say, Germany, we would probably be number three or four in that market if all our partners came with us because of the latent demand we have in the market.
It’s one of these things, like when I was at InterActive Corp, we bought this business called HomeAdvisor. It’s like, if you have jobs coming in, you can get contractors to fulfill the business. This is the same thing. There’s jobs coming in and people need to stay busy. They need to have the trucks rolling or they don’t make any money, so they’re happy to take these jobs from us and then from others.
My understanding was that Otonomo did a lot more than the preventative maintenance alerts, that they were trying to sell information back to the automakers. I think I was on a due diligence call at one time where you talked about, like, “We find these people are not using the CD player, so you don’t need to include the CD player,” or whatever. Is that part of the business going to continue or is it just focused on the roadside assistance and whatnot?
We did some program, some projects with the summary and it’s really helping them to understand how the customers are using the cars internally and externally. For example, whether customers like to drive or to shop, etc.
With some OEMs that the Urgently and Otonomo are very close to the discussions about doing some very interesting projects with data. It’ll be things that are more related to roadside assistance and I think in maintenance. I guess that hopefully soon we’ll be able to share some more information about it.
I think that’s right. The interesting thing about this business is that there’s no end to the opportunities, I think, we just have to focus on some things immediately. I think it’s this combination of the service network and then the connected car, and how do we bring these use cases to life and create revenue. There is a place for those like city data businesses, but today the revenue and the focus needs to be on where the scale is.
One of the interesting things around data that is starting to happen is also that until now, data was flowing outside of the car and we were using it. We start to see the OEMs implementing technology, also that you can send signals or commands to the car. You can remotely lock the car, remotely open the fuel hatch. Those things could be used in very interesting use cases also, in my opinion, around roadside assistance. Think about a world where you’re waiting for someone to rescue you. You can make sure that the car is locked so it’s safe, or if there was an accident, to unlock the car so they can come and rescue you remotely. Not only data is flowing out and of course becoming richer and richer, we start to see a world where you can also send back information or requests to the vehicles. I think those things could be really changing, also be used and change the roadside assistance market.
We do a lot of what you call lockout jobs, so someone loses their key and they can’t get in, right? What Ben’s talking about is it’s the perfect use case, which is you’re a fleet manager. You need to turn on the car on and off the car because you need to get cleaning services. Or in our case, if someone’s broken down, we call rideshare all the time to move people. We’ll get you in a car and get you somewhere safe. Just leave the vehicle. If we can do remote commands, like Ben’s talking about, to unlock the vehicle, you can just leave your car and it’s fine. Then we can take care of it and have it delivered to the dealer or wherever you want. That’s really the customer experience that it should be. You shouldn’t have to wait with your car for an hour or two hours. You should just get in an Uber and you should get back to where you’re going or take your kids to school or go to work or whatever you need to do, and the rest can be handled algorithmically with software. Those use cases are pretty important.
Interesting. Otonomo only has access to data in the car when you work with the automakers, whether they turned it on. Urgently is basically hoping to get outsourced. The automaker’s call center or something is receiving a call and then they forward it to you basically, or how does that work?
It depends. Some OEMs run their own call centers that they do for a whole bunch of reasons and some, we do for them. We can get a call or someone could hit the B call button in the car and increasingly what we’ll start to see is the car will call for help. This is the piece that’s probably the most critical if you think about this business in the future, which is it really is a software problem. You’d have to be able to digest and diagnose signals off a vehicle at basically a search speed, which is 100 milliseconds or less. You have to be really quick to figure out what’s going on with something.
This is what Ben’s team in Israel has excelled at as they’ve built these connections. We’re in the early innings of this, but you can imagine this really is a software play where it’s like the software becomes the key because you have to do super fast diagnostics like you would do on a search result.
Today, if you take your car in to the mechanic and they plug something into the OBD2 port, those things that they take 10 or 15 minutes to run the diagnostics depending on what it is or how complex. In the future, what’s going to come is, what Ben’s team has largely been working on is these super fast 100-millisecond returns for how do you process data at scale. That fundamentally is a software problem, and over time, when you mention the call center, the call center becomes less important and it’s more important to do things optimally online.
Interesting. Urgently is really improving the satisfaction of the consumers of a brand that either have encountered a problem or now via Otonomo can prevent from having that problem in the first place.
Here’s the way I’d phrase that, which is, if you think about any business, not this business. Think about the search business or the ad tech business as an example. The companies that sit in front of the consumer eyeballs that get the consumer to do the search first or go to the search page or whatever is the one to sit in front, like the first signal, those are the ones that control the downstream economics of almost everyone that comes after them. Like Google, they can decide what hotel aggregators get traffic. They can decide if TripAdvisor gets traffic. It’s really important to think about that in terms of the automotive business because what’s starting to happen is it used to be... I’ll use collision as an example. You get in an accident, your car will get impounded, you call your insurance company, and they would be the first ones to hear about it. Today, what’s starting to happen is the automotive company knows, the OEM knows, that the signals came off the car that there was an accident.
That may not sound like much, but it totally changes the paradigm of everything in the business because where it used to be a global insurance market would get the signal first and they could say go to this person and get a repair here. Now the OEM sits in front and they can say, “Well, I’m going to start selling insurance.” Tesla has something like an $800 million insurance business or something like that, and then all these other OEMs are going to roll out insurance companies. The reason they’re going to do that is because they are now sitting in the pole position to get the signal off the vehicle before anybody else. That’s why a lot of people talk about this. It’s like this race to get help with the vehicle data.
The reason that we’ve been successful is because we have a use case on the other end, which is it’s great to process something, but in the end, we have something where we can match a real-world service with it too.
That’s why, unlike just being a software company doing data processing, we can match what Ben has done with the service network and create real-world services around it.
When you think about this business and where it’s going, it really is like, “Who’s going to get the first signal, and what’s going to happen with it afterwards? How is that person that gets it going to control the downstream economics of everyone else that comes behind them?”
We did a dinner last night with CEO and CFO of LKQ. They were saying that they have a disagreement with the manufacturers. That the manufacturers believe that they own this data coming off the vehicle, whereas LKQ believes that it’s the owner of the vehicle. Maybe they’ve got some incentive because they say, “Why should the manufacturer be saying this is how the vehicle ought to be repaired?” They’re selling the repair parts and whatnot. I’m curious, who owns the data? Is it the manufacturer or the owner of the vehicle, etc.?
As people are probably aware, there are right-to-repair laws that have passed in some states. Massachusetts. I think the OEMs have said we shouldn’t give the access to people’s cars because there’s security issues with it. In the end, what’s going to happen is if your car is under warranty and you have a car that’s under warranty, it’s fine to let the OEM process it. In the end, the signal is going to start to get out to other places and it’s going to start to leak out. I think the OEMs will say they own the processing of it and they own the pipe. The consumers will say, “It’s my vehicle and I’m driving it, so I’m going to tell you that is my data.” Then the fleet companies will say, “We have the driver and we own the vehicle, so it’s our data.” I think it’s a pretty greenfield now.
If I can add, I think legally-wise, it’s very clear that the data belongs to the vehicle owner or the driver, depending on the continent or the country, that’s GDPR, CCPA, etc. But the OEMs are going to a big effort to get this data out of the vehicles. In my view, it’s a bit like our banks. It’s our money, but they are the custodians of our money. They invest it for us, they keep it safe for us, they create value out of it, and also take something in return. In my view, the OEMs have the same role because someone needs to pay AT&T for the SIM. Someone needs to pay Aptiv to put a modem inside. Someone needs to pay AWS to put the cloud to store the data. It’s our data, but they are an important part of the value chain.
You spoke a little bit about operational efficiency and the focus on the profitability. I have to imagine that variability of the job is an area that you would like to control, meaning you get a signal to go out to some place, you’ve got a dispatch, whether it’s tow truck, something happened with that vehicle. Where are you guys now with that? How does it feel in terms of your ability to diagnose that in order to have higher throughput, higher efficiencies in the business?
The piece that you’re talking about actually has the disablement reason. It has more to do with where the service fleet is at. We’ve spent the last probably 24 months building pretty sophisticated analytics around to predict, “It’s Super Bowl Sunday in a city. There’s a bad weather pattern. There’s really bad weather. What is it going to take to get someone out there to do it?” There is variability in this too. Again, I think you have to step back for a second. Our goal is to provide exceptional service. Sometimes we have to pay more to get someone out there and sometimes we have to pay less.
For the most part, letting the machine decide what the pricing should be in real-time is really efficient. It’s like airline pricing. You could imagine if instead of having a computer decide what your airline ticket would cost, some person in a call center would say, “You’re flying to New York? It’s going to be $450 for you today.” It’s just not efficient and you can’t do it in scale.
We run hundreds of thousands of jobs and they’re all dynamically priced basically in real-time based on all the analytics that we’ve run before, based on weather patterns, based on all kinds of things, to say, “In order to get someone to digitally accept this job at this price and provide this customer service score, this is exactly the price that we need to provide for it.”
We’re stunned actually at how efficient it’s been and how well it’s worked, and there’s more to come. It’s not only doing it for two years. There’s a lot more we’re going to do with it.
What’s next for Urgently? Is it to forge partnerships with OEMs primarily?
Yeah, I think we’re going to have partnerships with OEMs and insurance companies. There’s a lot of good cross-selling opportunity for things that Ben has already built and the Floow has already built. There’s going to be some synergistic things that we’ll start to announce in the next couple of quarters that we’re excited about.
The merger vote is coming up in a few weeks and then we close late September, mid-September. Then we have to start the planning process for next year. We want to start moving into more of these like Ben’s example of remote lock-unlock. It’s a great use case. There’s probably 12 of those that we’re thinking about that we’ll start to unveil. Some interesting things that are going to change how this service is delivered. That’s the next piece in terms of sales. It’s all about volume. All big OEMs, they all have roadside assistance businesses. It’s a small group of competitors out there in the US, small group globally. We’re out there talking to everybody, trying to sign up more and more and more of them.
The interesting thing about this business is, we’re at that point now where we’ve achieved enough scale and we’ve proven ourselves. It used to be some of these big automotive companies were like, “You’re too small. We need to wait till you prove it.” Now, we’re at a point where people are like, “We know you can do it because we’ve seen you do it for these other big companies so now we’re willing to take a shot with you.” We’re pretty excited about what’s coming.
Is the competition using software and its automated services or is it more just a person at a call center calling up individuals?
It’s a little both. A lot of it is call center. We started with technology first. We believe that we’re pretty far ahead. I think they’ll all start to say that they have software and they’re moving into that.
The difference was having a team that understands geospatial search and ad targeting. That business of how you optimize your ad spend across geolocations is very similar to this business. That is a pretty rare group of software people that can take that problem and say, “Here’s how you have algorithms and build geospatial targeting against it.” It’s very similar to this business. We believe we’re pretty far ahead of everyone else. In fact, when we start to put the data sets together between these companies, we believe that we’ll pull farther ahead. It’s a pretty big competitive moat.
After the merger is completed and then you start filing SCC filings as the new entity, then the world will basically learn more about Urgently at that point. You shared some things today but learn much more about the business versus what’s available in the public domain today.
That’s right. We expect to have our first earnings call mid-November. We already have SEC filings, so feel free if you’re bored on the weekend to go pore through them and start to pull them apart, if you don’t do that enough. Then more filings coming.
Great. Thank you very much. Please join me in thanking Matt and Ben.
Thank you, very much.
Thank you.
[applause]
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